1. Technical Field
This invention generally relates to computer question answering systems, and more specifically relates to using cohorts to infer additional attributes for an input case to provide a refined input case in the question answering system.
2. Background Art
A significant purpose for computer systems is the retrieval of relevant information or documents from a store of knowledge. The typical information retrieval system provides a document or file in response to a specific query or link. Question Answering (QA) is a specific type of information retrieval that deals with returning information in response to a natural language question. A QA response attempts to return a specific answer such as a word or phrase to a question such as “who”, “where” or “what”. One example of a QA system is the Deep Question Answering system, called “Watson”, developed by International Business Machines (IBM) Corporation of Armonk, N.Y. A user may submit a natural language question (also referred to as a case) to Watson, which will then provide an answer to the question based on an analysis of a corpus of information.
A QA system like Watson has application in the medical field due to the ability to process and relate large amounts of information. For example, QA can determine an appropriate cancer treatment for a patient based on the patient's medical history from knowledge stored in the database. While QA can identify knowledge stored in a large corpus using natural language processing to interpret the English language, it is not designed to provide an answer when knowledge is non-existent, such as when the corpus does not contain sufficient knowledge to answer the question. When a question is posed about a topic that is not available in a corpus, typically QA is at a loss to confidently answer the question.